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تحليل السيناريوهات البايزي×محاكاة مونت كارلو×
المجالالمحاكاةاتخاذ القرار
العائلةProcess / pipelineMCDM
سنة النشأة2000s1949
صاحب الطريقةDeveloped iteratively across Bayesian statistics and scenario planning communities; formalized in risk and decision analysis (Aven, Lempert et al., 2000s)Metropolis, N., Ulam, S.
النوعProbabilistic hybrid — Bayesian inference integrated with structured scenario analysisRobustness wrapper — Monte Carlo uncertainty propagation
المصدر التأسيسيAven, T., & Reniers, G. (2013). How to define and interpret a probability in a risk and safety setting. Safety Science, 51(1), 223–231. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
الأسماء البديلةBSA, Bayesian scenario planning, probabilistic scenario analysis, Bayesian-weighted scenario analysis
ذات صلة50
الملخصBayesian Scenario Analysis (BSA) combines structured scenario planning with Bayesian probability theory, assigning explicit prior probabilities to alternative futures and updating them as new evidence or expert judgments become available. The result is a probability-weighted distribution of outcomes across scenarios rather than a set of equally-weighted or arbitrarily-weighted futures.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateقارن الطرق: Bayesian Scenario Analysis · MONTE-CARLO-SIMULATION. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare